EPILOGUE

It has become increasingly important to provide attribution for low
frequency variations and change in Earth's climate. Whether this is
for improved scientific understanding, predictability assessment, or
to better inform societal planning and decision making, CDC is
dedicating increasing resources to climate change research. At CDC, we
seek to offer dynamical explanations for observed low frequency
variations and change, thereby drawing strongly upon our expertise on
seasonal to interannual variability, especially regarding air-sea
interactions and teleconnective influences.

A key challenge that we will pursue in CDC is to understand and
anticipate the regional characteristics of climate change. While there
is now little question that the climate has changed in a globally and
annually averaged sense, it is unclear what the local manifestations
of this are, nor do we appreciate their seasonal dependencies. Beyond
its relevancy to long term planning, this problem is of high relevance
to seasonal climate predictions. The fact is that the leading source
of US winter temperature skill in the 1990's is due to the so-called
optimal climate normals (OCN) tool, which we understand to be
essentially a trend prediction. It is necessary that a physical
explanation for such trends be given, and that they be clearly
distinguished from low frequency climatic variations. Most apparent of
these trends is the US wintertime surface warming, but other seasons
show a more complicated pattern for temperature and rainfall
change. We believe that progress can be made by improving our
understanding of the regional responses to the slow, systematic
changes in tropical oceans such as illustrated in Fig. 5.1, and we expect that much is to
be gained from our existing knowledge of the interannual impacts of
tropical forcing.

The change in the oceans itself is a problem that will focus future
CDC decadal climate research. The mean change in ocean temperatures is
a question that will require increased analysis of coupled
ocean-atmosphere models. We expect to partner with GFDL, NCAR and
other interested scientists to diagnose and understand the variability
in coupled model simulations, both natural and forced. We are
especially interested in the sensitivity of ENSO to climate change,
both its statistical properties and its interannual global impacts. A
related challenge is to understand whether the year-to-year
predictability of climate will change appreciably under the influence
of human-induced mean change. Will ENSO as an oceanic phenomena become
more predictable? Is it possible also that new regions will begin to
have useful ENSO-related climate predictability? Likewise, we would
like to understand whether the seasonal cycle of predictability will
change due to an altered mean climate. These questions, among others,
cut across time scales, and the greatest payoff in solving them may in
fact be to advance key problems on shorter time scales, such as
interannual prediction.